Cerebrovascular image preprocessing method

Abstract

The invention discloses a cerebrovascular image preprocessing method. The method comprises the following steps: acquiring a bright blood image and a black blood image of a brain blood vessel; with theblack blood image as a reference image and the bright blood image as a floating image, carrying out coordinate transformation on the bright blood image, and carrying out interpolation processing on the bright blood image by using a bilinear interpolation method; calculating the similarity between the bright blood image and the black blood image after interpolation processing by using similarity measurement; finding out the optimal similarity measurement by utilizing a search strategy; according to the space transformation matrix, carrying out coordinate transformation on the bright blood image when similarity measurement is optimal, and image registration is achieved; and according to the scanning area of the bright blood image, extracting the same scanning area in the black blood image to obtain a common region of interest of the bright blood image and the black blood image. According to the scheme, a doctor can be helped to accurately diagnose intracranial diseases.

Description

technical field [0001] The technical field of image processing of the present invention particularly relates to a method for preprocessing cerebrovascular images, electronic equipment, and a computer-readable storage medium. Background technique [0002] With the development of medical imaging technology, a variety of acquisition devices and imaging modes of medical images are emerging, which also brings the need for effective combination of medical images obtained from different medical devices or different acquisition modes of the same medical device. Promoted the development of medical image registration technology. [0003] Medical image registration technology can analyze the imaging results of the same patient from a single or multiple imaging modes. The registration images need to reflect different anatomical or functional information of the human body in the same coordinate system or on the same benchmark. There is no need for doctors to realize image space transfor...

AI Technical Summary

Problems solved by technology

[0004] However, due to the complex tissue structure in the human body, the variety of organs, the adhesion between organs, or the movement of organs caused by the breathing movement of the human body, and the limitations of imaging equipment, medical images will appear blurred and the gray distribution is uneven. The edges of organs are not clear, and there are many artifacts. Secondly, the images of the same organ from different individuals are also very different. At the same time, the use of different equipment and deviations in imaging angles during the imaging process will also cause different individuals to have the same organ. Different representations of organs in imaging; in addition, the same organ in MRI images in different sequence scans also has problems such as shape brightness, resolution, and position and direction.

Images